Built and scaled an AI-powered e-learning platform for 100K+ users, delivering secure video streaming, responsive dashboards, and real-time learning analytics.

• Developed and scaled the E-Learning platform from 5K to 100K+ users, enhancing performance and reliability across web and mobile clients.

• Architected and optimized adaptive bitrate video streaming using AWS S3, CloudFront, and HLS, reducing buffering by 40% and achieving 99.97% uptime for 100K+ active users.

• Built React.js + TypeScript dashboards with lazy loading and API caching, improving page load speed by 35% and cutting network payload by 30%.

• Integrated GraphQL APIs to replace REST endpoints, streamlining data fetching and reducing over-fetching by 25%.

• Enhanced API performance through query optimization and caching, supporting up to 2K+ concurrent requests with sub-300ms response times.

• Implemented server-driven UI components, enabling feature experimentation without redeployments and accelerating A/B testing cycles by 50%.

• Deployed CI/CD pipelines via GitHub Actions and Docker, reducing deployment times from hours to under 15 minutes.

• Added AWS CloudWatch observability and structured event logging, decreasing mean-time-to-detect (MTTD) by 30% for production incidents.

• Collaborated with AI teams to integrate LangChain and OpenAI API into a student-facing chatbot, cutting manual support tickets by 25%.

• Partnered with design and product to deliver accessibility-compliant, responsive UIs, increasing student satisfaction scores

by 18%.

Developed full-stack healthcare analytics tools for real-time patient monitoring, improving data performance, system reliability, and deployment efficiency.

• Developed a responsive React + TypeScript dashboard for healthcare analytics, improving engagement by 20%.

• Refactored legacy JavaScript into modular TypeScript components, reducing bugs by 35%.

• Optimized API workflows and caching, cutting data-fetch latency by 30%.

• Tuned performance with Webpack and Lighthouse audits to sustain 60 FPS rendering.

• Collaborated with backend engineers to design RESTful endpoints in Node.js, improving data reliability and synchronization.

• Implemented CI/CD pipelines with GitHub Actions, reducing deployment time by 40% and improving release consistency.

Engineered scalable geospatial tracking systems for 300K+ devices, optimizing APIs, dashboards, and map-based data visualization for high performance and uptime.

• Scaled a real-time asset tracking system from 2K to 300K+ active users, optimizing data flow, backend throughput, and frontend rendering speed.

• Re-architected Google Maps API integrations using asynchronous updates and WebSockets, reducing map refresh latency by 60% and supporting 10K+ simultaneous updates.

• Migrated API infrastructure to Node.js microservices with Redis caching, achieving sub-200ms average response time and improving scalability by 5×.

• Implemented sharded PostgreSQL database models and load balancing with NGINX, sustaining 10× growth in concurrent traffic without downtime.

• Built interactive D3.js and Recharts dashboards for visualizing 100K+ tracked devices, increasing system usability scores by 30% among field operators.

• Containerized services using Docker and deployed auto-scaling infrastructure on AWS EC2, maintaining 99.9% uptime during peak operations.

• Optimized geospatial query performance through indexing and parallelization, reducing computation time by 45% for complex multi-region queries.

• Enhanced frontend code efficiency by modularizing React components, cutting redundant re-renders by 25% and improving maintainability.

• Collaborated with product and client teams to implement multi-tenant user management and secure API authentication, ensuring 100% compliance with enterprise data standards.